Spaces:
Runtime error
Runtime error
""" | |
Advanced Agentic System Interface | |
------------------------------- | |
Provides a chat interface to interact with the autonomous agent teams: | |
- Team A: Coders (App/Software Developers) | |
- Team B: Business (Entrepreneurs) | |
- Team C: Research (Deep Online Research) | |
- Team D: Crypto & Sports Trading | |
""" | |
import gradio as gr | |
from fastapi import FastAPI, HTTPException | |
from fastapi.middleware.cors import CORSMiddleware | |
import uvicorn | |
from typing import Dict, Any, List, Tuple, Optional | |
import logging | |
from pathlib import Path | |
import asyncio | |
from datetime import datetime | |
import json | |
from requests.adapters import HTTPAdapter, Retry | |
from urllib3.util.retry import Retry | |
import time | |
from agentic_system import AgenticSystem | |
from team_management import TeamManager, TeamType, TeamObjective | |
from orchestrator import AgentOrchestrator | |
from reasoning import UnifiedReasoningEngine as ReasoningEngine | |
# Configure logging | |
logging.basicConfig(level=logging.INFO) | |
logger = logging.getLogger(__name__) | |
# Configure network settings | |
TIMEOUT = int(os.getenv('REQUESTS_TIMEOUT', '30')) | |
MAX_RETRIES = 5 | |
RETRY_BACKOFF = 1 | |
def setup_requests_session(): | |
"""Configure requests session with retries.""" | |
session = requests.Session() | |
retry_strategy = Retry( | |
total=MAX_RETRIES, | |
backoff_factor=RETRY_BACKOFF, | |
status_forcelist=[408, 429, 500, 502, 503, 504], | |
allowed_methods=["HEAD", "GET", "PUT", "DELETE", "OPTIONS", "TRACE"] | |
) | |
adapter = HTTPAdapter(max_retries=retry_strategy) | |
session.mount("https://", adapter) | |
session.mount("http://", adapter) | |
return session | |
def check_network(max_attempts=3): | |
"""Check network connectivity with retries.""" | |
session = setup_requests_session() | |
for attempt in range(max_attempts): | |
try: | |
# Try multiple DNS servers | |
for dns in ['8.8.8.8', '8.8.4.4', '1.1.1.1']: | |
try: | |
socket.gethostbyname('huggingface.co') | |
break | |
except socket.gaierror: | |
continue | |
# Test connection to Hugging Face | |
response = session.get('https://huggingface.co/api/health', | |
timeout=TIMEOUT) | |
if response.status_code == 200: | |
return True | |
except (requests.RequestException, socket.gaierror) as e: | |
logger.warning(f"Network check attempt {attempt + 1} failed: {e}") | |
if attempt < max_attempts - 1: | |
time.sleep(RETRY_BACKOFF * (attempt + 1)) | |
continue | |
logger.error("Network connectivity check failed after all attempts") | |
return False | |
class ChatInterface: | |
def __init__(self): | |
# Check network connectivity | |
if not check_network(): | |
logger.warning("Network connectivity issues detected - continuing with degraded functionality") | |
# Initialize core components with consistent configuration | |
config = { | |
"min_confidence": 0.7, | |
"parallel_threshold": 3, | |
"learning_rate": 0.1, | |
"strategy_weights": { | |
"LOCAL_LLM": 0.8, | |
"CHAIN_OF_THOUGHT": 0.6, | |
"TREE_OF_THOUGHTS": 0.5, | |
"META_LEARNING": 0.4 | |
} | |
} | |
self.orchestrator = AgentOrchestrator(config) | |
self.agentic_system = AgenticSystem(config) | |
self.team_manager = TeamManager(self.orchestrator) | |
self.chat_history = [] | |
self.active_objectives = {} | |
# Set up network session | |
self.session = setup_requests_session() | |
# Initialize teams | |
asyncio.run(self.team_manager.initialize_team_agents()) | |
async def process_message( | |
self, | |
message: str, | |
history: List[List[str]] | |
) -> Tuple[str, List[List[str]]]: | |
"""Process incoming chat message.""" | |
try: | |
# Update chat history | |
self.chat_history = history | |
# Process message | |
response = await self._handle_message(message) | |
# Update history | |
if response: | |
history.append([message, response]) | |
return response, history | |
except Exception as e: | |
logger.error(f"Error processing message: {str(e)}") | |
error_msg = "I apologize, but I encountered an error. Please try again." | |
history.append([message, error_msg]) | |
return error_msg, history | |
async def _handle_message(self, message: str) -> str: | |
"""Handle message processing with error recovery.""" | |
try: | |
# Analyze intent | |
intent = await self._analyze_intent(message) | |
intent_type = self._get_intent_type(intent) | |
# Route to appropriate handler | |
if intent_type == "query": | |
return await self._handle_query(message) | |
elif intent_type == "objective": | |
return await self._handle_objective(message) | |
elif intent_type == "status": | |
return await self._handle_status_request(message) | |
else: | |
return await self._handle_general_chat(message) | |
except Exception as e: | |
logger.error(f"Error in message handling: {str(e)}") | |
return "I apologize, but I encountered an error processing your message. Please try again." | |
def _get_intent_type(self, intent) -> str: | |
"""Safely extract intent type from various result formats.""" | |
if isinstance(intent, dict): | |
return intent.get("type", "general") | |
return "general" | |
async def _analyze_intent(self, message: str) -> Dict[str, Any]: | |
"""Analyze user message intent with error handling.""" | |
try: | |
# Use reasoning engine to analyze intent | |
analysis = await self.orchestrator.reasoning_engine.reason( | |
query=message, | |
context={ | |
"chat_history": self.chat_history, | |
"active_objectives": self.active_objectives | |
} | |
) | |
return { | |
"type": analysis.get("intent_type", "general"), | |
"confidence": analysis.get("confidence", 0.5), | |
"entities": analysis.get("entities", []), | |
"action_required": analysis.get("action_required", False) | |
} | |
except Exception as e: | |
logger.error(f"Error analyzing intent: {str(e)}") | |
return {"type": "general", "confidence": 0.5} | |
async def _handle_query(self, message: str) -> str: | |
"""Handle information queries.""" | |
try: | |
# Get relevant teams for the query | |
recommended_teams = await self.team_manager.get_team_recommendations(message) | |
# Get responses from relevant teams | |
responses = [] | |
for team_type in recommended_teams: | |
response = await self._get_team_response(team_type, message) | |
if response: | |
responses.append(response) | |
if not responses: | |
return "I apologize, but I couldn't find a relevant answer to your query." | |
# Combine and format responses | |
return self._format_team_responses(responses) | |
except Exception as e: | |
logger.error(f"Error handling query: {str(e)}") | |
return "I apologize, but I encountered an error processing your query. Please try again." | |
async def _handle_objective(self, message: str) -> str: | |
"""Handle new objective creation.""" | |
try: | |
# Create new objective | |
objective_id = await self.team_manager.create_objective(message) | |
if not objective_id: | |
return "I apologize, but I couldn't create the objective. Please try again." | |
# Format and return response | |
return self._format_objective_creation(objective_id) | |
except Exception as e: | |
logger.error(f"Error creating objective: {str(e)}") | |
return "I apologize, but I encountered an error creating the objective. Please try again." | |
async def _handle_status_request(self, message: str) -> str: | |
"""Handle status check requests.""" | |
try: | |
# Get system status | |
system_status = await self.agentic_system.get_system_status() | |
# Get team status | |
team_status = {} | |
for team_id, team in self.team_manager.teams.items(): | |
team_status[team.name] = await self.team_manager.monitor_objective_progress(team_id) | |
# Get objective status | |
objective_status = {} | |
for obj_id, obj in self.active_objectives.items(): | |
objective_status[obj_id] = await self.team_manager.monitor_objective_progress(obj_id) | |
return self._format_status_response(system_status, team_status, objective_status) | |
except Exception as e: | |
logger.error(f"Error getting status: {str(e)}") | |
return "I apologize, but I encountered an error getting the status. Please try again." | |
async def _handle_general_chat(self, message: str) -> str: | |
"""Handle general chat interactions with error recovery.""" | |
try: | |
# Use reasoning engine for response generation | |
response = await self.orchestrator.reasoning_engine.reason( | |
query=message, | |
context={ | |
"chat_history": self.chat_history, | |
"system_state": await self.agentic_system.get_system_status() | |
} | |
) | |
if not response or not response.get("response"): | |
return "I apologize, but I couldn't generate a meaningful response. Please try again." | |
return response["response"] | |
except Exception as e: | |
logger.error(f"Error in general chat: {str(e)}") | |
return "I apologize, but I encountered an error processing your message. Please try again." | |
async def _get_team_response(self, team_type: TeamType, query: str) -> Dict[str, Any]: | |
"""Get response from a specific team.""" | |
try: | |
team = self.team_manager.teams.get(team_type.value) | |
if not team: | |
return None | |
# Get response from team's agents | |
responses = [] | |
for agent in team.agents: | |
response = await agent.process_query(query) | |
if response: | |
responses.append(response) | |
if not responses: | |
return None | |
# Return best response | |
return self._combine_agent_responses(responses) | |
except Exception as e: | |
logger.error(f"Error getting team response: {str(e)}") | |
return None | |
def _combine_agent_responses(self, responses: List[Dict[str, Any]]) -> Dict[str, Any]: | |
"""Combine multiple agent responses into a coherent response.""" | |
try: | |
# Sort by confidence | |
valid_responses = [ | |
r for r in responses | |
if r.get("success", False) and r.get("response") | |
] | |
if not valid_responses: | |
return None | |
sorted_responses = sorted( | |
valid_responses, | |
key=lambda x: x.get("confidence", 0), | |
reverse=True | |
) | |
# Take the highest confidence response | |
return sorted_responses[0] | |
except Exception as e: | |
logger.error(f"Error combining responses: {str(e)}") | |
return None | |
def _format_team_responses(self, responses: List[Dict[str, Any]]) -> str: | |
"""Format team responses into a readable message.""" | |
try: | |
if not responses: | |
return "No team responses available." | |
formatted = [] | |
for resp in responses: | |
if resp and resp.get("response"): | |
team_name = resp.get("team_name", "Unknown Team") | |
confidence = resp.get("confidence", 0) | |
formatted.append( | |
f"\n{team_name} (Confidence: {confidence:.2%}):\n{resp['response']}" | |
) | |
if not formatted: | |
return "No valid team responses available." | |
return "\n".join(formatted) | |
except Exception as e: | |
logger.error(f"Error formatting responses: {str(e)}") | |
return "Error formatting team responses." | |
def _format_objective_creation(self, objective_id: str) -> str: | |
"""Format objective creation response.""" | |
try: | |
obj = self.active_objectives.get(objective_id) | |
if not obj: | |
return "Objective created but details not available." | |
return "\n".join([ | |
"New Objective Created:", | |
f"Description: {obj['description']}", | |
f"Status: {obj['status']}", | |
f"Assigned Teams: {', '.join(t.value for t in obj['teams'])}" | |
]) | |
except Exception as e: | |
logger.error(f"Error formatting objective: {str(e)}") | |
return "Error formatting objective details." | |
def _format_status_response( | |
self, | |
system_status: Dict[str, Any], | |
team_status: Dict[str, Any], | |
objective_status: Dict[str, Any] | |
) -> str: | |
"""Format status response.""" | |
try: | |
# Format system status | |
status = [ | |
"System Status:", | |
f"- State: {system_status['state']}", | |
f"- Active Agents: {system_status['agent_count']}", | |
f"- Active Tasks: {system_status['active_tasks']}", | |
"\nTeam Status:" | |
] | |
# Add team status | |
for team_name, team_info in team_status.items(): | |
status.extend([ | |
f"\n{team_name}:", | |
f"- Active Agents: {team_info['active_agents']}", | |
f"- Completion Rate: {team_info['completion_rate']:.2%}", | |
f"- Collaboration Score: {team_info['collaboration_score']:.2f}" | |
]) | |
# Add objective status | |
if objective_status: | |
status.append("\nActive Objectives:") | |
for obj_id, obj_info in objective_status.items(): | |
obj = self.active_objectives[obj_id] | |
status.extend([ | |
f"\n{obj['description']}:", | |
f"- Status: {obj['status']}", | |
f"- Teams: {', '.join(t.value for t in obj['teams'])}", | |
f"- Progress: {sum(t['completion_rate'] for t in obj_info.values())/len(obj_info):.2%}" | |
]) | |
return "\n".join(status) | |
except Exception as e: | |
logger.error(f"Error formatting status: {str(e)}") | |
return "Error formatting status information." | |
class VentureUI: | |
def __init__(self, app): | |
self.app = app | |
def create_interface(self): | |
"""Create the Gradio interface.""" | |
with gr.Blocks( | |
theme=gr.themes.Soft(), | |
analytics_enabled=False, | |
title="Advanced Agentic System" | |
) as interface: | |
# Verify Gradio version | |
gr.Markdown(f""" | |
# Advanced Agentic System Chat Interface v{gr.__version__} | |
Chat with our autonomous agent teams: | |
- Team A: Coders (App/Software Developers) | |
- Team B: Business (Entrepreneurs) | |
- Team C: Research (Deep Online Research) | |
- Team D: Crypto & Sports Trading | |
You can: | |
1. Ask questions | |
2. Create new objectives | |
3. Check status of teams and objectives | |
4. Get insights and recommendations | |
""") | |
chatbot = gr.Chatbot( | |
label="Chat History", | |
height=400, | |
bubble_full_width=False, | |
show_copy_button=True, | |
render_markdown=True | |
) | |
with gr.Row(): | |
msg = gr.Textbox( | |
label="Message", | |
placeholder="Chat with the Agentic System...", | |
lines=2, | |
scale=9, | |
autofocus=True, | |
container=True | |
) | |
submit = gr.Button( | |
"Send", | |
scale=1, | |
variant="primary" | |
) | |
with gr.Row(): | |
clear = gr.ClearButton( | |
[msg, chatbot], | |
value="Clear Chat", | |
variant="secondary", | |
scale=1 | |
) | |
retry = gr.Button( | |
"Retry Last", | |
variant="secondary", | |
scale=1 | |
) | |
async def respond(message, history): | |
try: | |
# Convert history to the format expected by process_message | |
history_list = [[x, y] for x, y in history] if history else [] | |
response, history_list = await self.app(message, history_list) | |
# Update history | |
if history is None: | |
history = [] | |
history.append((message, response)) | |
return "", history | |
except Exception as e: | |
logger.error(f"Error in chat response: {str(e)}") | |
error_msg = "I apologize, but I encountered an error. Please try again." | |
if history is None: | |
history = [] | |
history.append((message, error_msg)) | |
return "", history | |
async def retry_last(history): | |
if not history: | |
return history | |
last_user_msg = history[-1][0] | |
history = history[:-1] # Remove last exchange | |
return await respond(last_user_msg, history) | |
msg.submit( | |
respond, | |
[msg, chatbot], | |
[msg, chatbot], | |
api_name="chat" | |
).then( | |
lambda: gr.update(interactive=True), | |
None, | |
[msg, submit], | |
queue=False | |
) | |
submit.click( | |
respond, | |
[msg, chatbot], | |
[msg, chatbot], | |
api_name="submit" | |
).then( | |
lambda: gr.update(interactive=True), | |
None, | |
[msg, submit], | |
queue=False | |
) | |
retry.click( | |
retry_last, | |
[chatbot], | |
[chatbot], | |
api_name="retry" | |
) | |
# Event handlers for better UX | |
msg.change(lambda x: gr.update(interactive=bool(x.strip())), [msg], [submit]) | |
# Add example inputs | |
gr.Examples( | |
examples=[ | |
"What can Team A (Coders) help me with?", | |
"Create a new objective: Analyze market trends", | |
"What's the status of all teams?", | |
"Give me insights about recent developments" | |
], | |
inputs=msg, | |
label="Example Queries" | |
) | |
return interface | |
def create_chat_interface() -> gr.Blocks: | |
"""Create Gradio chat interface.""" | |
chat = ChatInterface() | |
ui = VentureUI(chat.process_message) | |
return ui.create_interface() | |
# Initialize FastAPI | |
app = FastAPI( | |
title="Advanced Agentic System", | |
description="Venture Strategy Optimizer with OpenAI-compatible API", | |
version="1.0.0" | |
) | |
# Add CORS middleware | |
app.add_middleware( | |
CORSMiddleware, | |
allow_origins=["*"], | |
allow_credentials=True, | |
allow_methods=["*"], | |
allow_headers=["*"], | |
) | |
# Include OpenAI-compatible routes | |
from api.openai_compatible import OpenAICompatibleAPI | |
reasoning_engine = UnifiedReasoningEngine() | |
openai_api = OpenAICompatibleAPI(reasoning_engine) | |
app.include_router(openai_api.router, tags=["OpenAI Compatible"]) | |
# Original API routes | |
async def health_check(): | |
"""Health check endpoint.""" | |
return { | |
"status": "healthy", | |
"version": "1.0.0", | |
"endpoints": { | |
"openai_compatible": "/v1/chat/completions", | |
"venture": "/api/venture", | |
"ui": "/" | |
} | |
} | |
async def reason(query: str, context: Optional[Dict[str, Any]] = None): | |
"""Reasoning endpoint.""" | |
try: | |
result = await reasoning_engine.reason(query, context or {}) | |
return result | |
except Exception as e: | |
logger.error(f"Reasoning error: {e}") | |
raise HTTPException(status_code=500, detail=str(e)) | |
async def analyze_venture( | |
venture_type: str, | |
description: str, | |
metrics: Optional[Dict[str, Any]] = None | |
): | |
"""Venture analysis endpoint.""" | |
try: | |
result = await VentureAPI(reasoning_engine).analyze_venture( | |
venture_type=venture_type, | |
description=description, | |
metrics=metrics or {} | |
) | |
return result | |
except Exception as e: | |
logger.error(f"Analysis error: {e}") | |
raise HTTPException(status_code=500, detail=str(e)) | |
async def get_venture_types(): | |
"""Get available venture types.""" | |
return VentureAPI(reasoning_engine).get_venture_types() | |
# Create Gradio interface | |
interface = create_chat_interface() | |
# Mount Gradio app to FastAPI | |
app = gr.mount_gradio_app(app, interface, path="/") | |
if __name__ == "__main__": | |
# Run with uvicorn when called directly | |
uvicorn.run( | |
"app:app", | |
host="0.0.0.0", | |
port=7860, | |
reload=True, | |
workers=4 | |
) | |